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Tell Me Who I Am: An Interactive Recommendation System

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Abstract

We consider a model of recommendation systems, where each member from a given set of players has a binary preference to each element in a given set of objects: intuitively, each player either likes or dislikes each object. However, the players do not know their preferences. To find his preference of an object, a player may probe it, but each probe incurs unit cost. The goal of the players is to learn their complete preference vector (approximately) while incurring minimal cost. This is possible if many players have similar preference vectors: such a set of players with similar “taste” may split the cost of probing all objects among them, and share the results of their probes by posting them on a public billboard. The problem is that players do not know a priori whose taste is close to theirs. In this paper we present a distributed randomized peer-to-peer algorithm in which each player outputs a vector which is close to the best possible approximation of the player’s real preference vector after a polylogarithmic number of rounds. The algorithm works under adversarial preferences. Previous algorithms either made severely limiting assumptions on the structure of the preference vectors, or had polynomial overhead.

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Authors and Affiliations

  1. Schools of Mathematics and Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel

    Noga Alon

  2. IAS, Princeton, NJ, 08540, USA

    Noga Alon

  3. Dept. of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Baruch Awerbuch

  4. School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel

    Yossi Azar

  5. School of Electrical Engineering, Tel Aviv University, Tel Aviv, 69978, Israel

    Boaz Patt-Shamir

Authors
  1. Noga Alon
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  2. Baruch Awerbuch
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  3. Yossi Azar
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  4. Boaz Patt-Shamir
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Corresponding author

Correspondence to Boaz Patt-Shamir.

Additional information

Research of N. Alon supported in part by the Israel Science Foundation and by the Von Neumann Fund. B. Awerbuch supported by NSF grants ANIR-0240551, CCF-0515080 and CCR-0311795. Research of Y. Azar supported in part by the German-Israeli Foundation and by the Israel Science Foundation. Research of B. Patt-Shamir supported in part by Israel Ministry of Science and Technology and by the Israel Science Foundation (grant 664/05).

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Alon, N., Awerbuch, B., Azar, Y. et al. Tell Me Who I Am: An Interactive Recommendation System. Theory Comput Syst 45, 261–279 (2009). https://doi.org/10.1007/s00224-008-9100-7

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  • DOI: https://doi.org/10.1007/s00224-008-9100-7

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